(182l) Investigating LecA Binding Mechanisms with a Cellular Membrane Containing Multiple Types of Receptors Via Kinetic Monte Carlo Simulation

Pseudomonas aeruginosa is a widespread bacterium that causes various acute and chronic infections such as pneumonia and meningitis [1]. LecA protein is one of the adhesins that mediate P. aeruginosa attachment to a host cell membrane, leading to the development of the infection [2]. LecA is a homotetramer that consists of four identical binding units. The four binding sites are grouped into two pairs that are aligned in opposite directions. Hence, one LecA can bind to maximum two glycolipid receptors at a time on a cell membrane. Moreover, in contrast to the classic antigen-antibody interaction, LecA can simultaneously bind to various types of glycolipids with different affinities. These two distinct characteristics, multivalency and semi-specificity, make the LecA recognition principle inherently different from classic bimolecular interactions (e.g. antibody-antigen binding).

Our recent study has experimentally demonstrated that mixing different glycolipid receptors on cell membranes could results in the alternation of LecA binding capacity, avidity, and kinetics, which influence the downstream biological processes. However, no theoretical model can interpret the complex interplay between LecA and multiple glycolipids. Here, we aim to develop a kinetic Monte Carlo model (kMC) to simulate the kinetics of LecA binding to a cell membrane containing two types of receptors. The kMC framework is selected as it can track the temporal evolution of the surface configuration, which is important in the overall binding kinetics on a cell membrane [4]. Specifically, we represent a cell membrane as square lattices, where LecA receptors reside and are allowed to migrate; on the other hand, LecA are allowed to attach and detach from the simulation lattices during the simulation. The overall binding kinetics are represented by a few discrete events in the proposed kMC: (a) the attachment of a LecA protein (b) the detachment of a membrane-bound LecA protein (c) surface reactions between membrane-bound LecA proteins with receptors (d) receptor migration on a membrane. During the simulation, reaction rates of these events, which depend on the surface configuration, are calculated to randomly select one event to be performed at a time until the pre-specified end time. For the computational efficiency, the receptor migration event is decoupled as the rate of the receptor migration is overwhelmingly large [5]. We apply this methodology to systematically analyze the overall binding process and identify the most important factors. The kMC simulation not only supports our experimental results, but also offers a fundamental mechanism to predict the complex glycobiology processes on cell membrane surface.

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